Chou Kuo-Chen
Gordon Life Science Institute, Boston, Massachusetts 02478, USA and Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah 21589, Saudi Arabia.
Med Chem. 2015;11(3):218-34. doi: 10.2174/1573406411666141229162834.
Facing the explosive growth of biological sequence data, such as those of protein/peptide and DNA/RNA, generated in the post-genomic age, many bioinformatical and mathematical approaches as well as physicochemical concepts have been introduced to timely derive useful informations from these biological sequences, in order to stimulate the development of medical science and drug design. Meanwhile, because of the rapid penetrations from these disciplines, medicinal chemistry is currently undergoing an unprecedented revolution. In this minireview, we are to summarize the progresses by focusing on the following six aspects. (1) Use the pseudo amino acid composition or PseAAC to predict various attributes of protein/peptide sequences that are useful for drug development. (2) Use pseudo oligonucleotide composition or PseKNC to do the same for DNA/RNA sequences. (3) Introduce the multi-label approach to study those systems where the constituent elements bear multiple characters and functions. (4) Utilize the graphical rules and "wenxiang" diagrams to analyze complicated biomedical systems. (5) Recent development in identifying the interactions of drugs with its various types of target proteins in cellular networking. (6) Distorted key theory and its application in developing peptide drugs.
面对后基因组时代产生的生物序列数据（如蛋白质/肽和DNA/RNA序列数据）的爆炸式增长，人们引入了许多生物信息学和数学方法以及物理化学概念，以便及时从这些生物序列中获取有用信息，从而推动医学科学和药物设计的发展。与此同时，由于这些学科的迅速渗透，药物化学目前正在经历一场前所未有的变革。在这篇微型综述中，我们将通过关注以下六个方面来总结进展情况。（1）使用伪氨基酸组成（PseAAC）来预测对药物开发有用的蛋白质/肽序列的各种属性。（2）对DNA/RNA序列使用伪寡核苷酸组成（PseKNC）来做同样的事情。（3）引入多标签方法来研究那些组成元素具有多种特征和功能的系统。（4）利用图形规则和“wenxiang”图来分析复杂的生物医学系统。（5）细胞网络中药物与其各种类型靶蛋白相互作用识别的最新进展。（6）扭曲关键理论及其在肽类药物开发中的应用。
